Sensitivity to pain expectations: A Bayesian model of individual differences.

The thoughts and feelings people have about pain (referred to as 'pain expectations') are known to alter the perception of pain. However little is known about the cognitive processes that underpin pain expectations, or what drives the differing effect that pain expectations have between individuals. This paper details the testing of a model of pain perception which formalises the response to pain in terms of a Bayesian prior-to-posterior updating process. Using data acquired from a short and deception-free predictive cue task, it was found that this Bayesian model predicted ratings of pain better than other, simpler models. At the group level, the results confirmed two core predictions of predictive coding; that expectation alters perception, and that increased uncertainty in the expectation reduces its impact on perception. The addition of parameters relating to trait differences in pain expectation improved the fit of the model, suggesting that such traits play a significant role in perception above and beyond the influence of expectations triggered by predictive cues. When the model parameters were allowed to vary by participant, the model's fit improved further. This final model produced a characterisation of each individual's sensitivity to pain expectations. This model is relevant for the understanding of the cognitive basis of pain expectations and could potentially act as a useful tool for guiding patient stratification and clinical experimentation.

Mapping the platelet profile for functional genomic studies and demonstration of the effect size of the GP6 locus.

BACKGROUND: Evidence suggests the wide variation in platelet response within the population is genetically controlled. Unraveling the complex relationship between sequence variation and platelet phenotype requires accurate and reproducible measurement of platelet response. OBJECTIVE: To develop a methodology suitable for measuring signaling pathway-specific platelet phenotype, to use this to measure platelet response in a large cohort, and to demonstrate the effect size of sequence variation in a relevant model gene. METHODS: Three established platelet assays were evaluated: mobilization of [Ca(2+)](i), aggregometry and flow cytometry, each in response to adenosine 5'-diphosphate (ADP) or the glycoprotein (GP) VI-specific crosslinked collagen-related peptide (CRP). Flow cytometric measurement of fibrinogen binding and P-selectin expression in response to a single, intermediate dose of each agonist gave the best combination of reproducibility and inter-individual variability and was used to measure the platelet response in 506 healthy volunteers. Pathway specificity was ensured by blocking the main subsidiary signaling pathways. RESULTS: Individuals were identified who were hypo- or hyper-responders for both pathways, or who had differential responses to the two agonists, or between outcomes. 89 individuals, retested three months later using the same methodology, showed high concordance between the two visits in all four assays (r(2) = 0.872, 0.868, 0.766 and 0.549); all subjects retaining their phenotype at recall. The effect of sequence variation at the GP6 locus accounted for approximately 35% of the variation in the CRP-XL response. CONCLUSION: Genotyping-phenotype association studies in a well-characterized, large cohort provides a powerful strategy to measure the effect of sequence variation in genes regulating the platelet response.

Bayesian trio models for association in the presence of genotyping errors.

Errors in genotyping can greatly affect family-based association studies. If a mendelian inconsistency is detected, the family is usually removed from the analysis. This reduces power, and may introduce bias. In addition, a large proportion of genotyping errors remain undetected, and these also reduce power. We present a Bayesian framework for performing association studies with SNP data on samples of trios consisting of parents with an affected offspring, while allowing for the presence of both detectable and undetectable genotyping errors. This framework also allows for the inclusion of missing genotypes. Associations between the SNP and disease were modelled in terms of the genotypic relative risks. The performances of the analysis methods were investigated under a variety of models for disease association and genotype error, looking at both power to detect association and precision of genotypic relative risk estimates. As expected, power to detect association decreased as genotyping error probability increased. Importantly, however, analyses allowing for genotyping error had similar power to standard analyses when applied to data without genotyping error. Furthermore, allowing for genotyping error yielded relative risk estimates that were approximately unbiased, together with 95% credible intervals giving approximately correct coverage. The methods were also applied to a real dataset: a sample of schizophrenia cases and their parents genotyped at SNPs in the dysbindin gene. The analysis methods presented here require no prior information on the genotyping error probabilities, and may be fitted in WinBUGS.

Predicting secondary progression in relapsing-remitting multiple sclerosis: a Bayesian analysis.

With the aid of a Bayesian statistical model of the natural course of relapsing remitting Multiple Sclerosis (MS), we identify short-term clinical predictors of long-term evolution of the disease, with particular focus on predicting onset of secondary progressive course (failure event) on the basis of patient information available at an early stage of disease. The model specifies the full joint probability distribution for a set of variables including early indicator variables (observed during the early stage of disease), intermediate indicator variables (observed throughout the course of disease, prefailure) and the time to failure. Our model treats the intermediate indicators as a surrogate response event, so that in right-censored patients, these indicators provide supplementary information pointing towards the unobserved failure times. Moreover, the full probability modelling approach allows the considerable uncertainty which affects certain early indicators, such as the early relapse rates, to be incorporated in the analysis. With such a model, the ability of early indicators to predict failure can be assessed more accurately and reliably, and explained in terms of the relationship between early and intermediate indicators. Moreover, a model with the aforementioned features allows us to characterize the pattern of disease course in high-risk patients, and to identify short-term manifestations which are strongly related to long-term evolution of disease, as potential surrogate responses in clinical trials. Our analysis is based on longitudinal data from 186 MS patients with a relapsing-remitting initial course. The following important early predictors of the time to progression emerged: age; number of neurological functional systems (FSs) involved; sphincter, or motor, or motor-sensory symptoms; presence of sequelae after onset. During the first 3 years of follow up, to reach EDSS> or =4 outside relapse, to have sphincter or motor relapses and to reach moderate pyramidal involvement were also found to be unfavourable prognostic factors.

Usefulness of Bayesian graphical models for early prediction of disease progression in multiple sclerosis.

Previous studies of possible prognostic indicators for multiple sclerosis have been based on "classic" Cox's proportional hazards regression model, as well as on equivalent or simpler approaches, restricting their attention to variables measured either at disease onset or at a few points during follow-up. The aim of our study was to analyse the risk of reaching secondary progression in MS patients with a relapsing-remitting initial course, using two different statistical approaches: a Cox's proportional-hazards model and a Bayesian latent-variable model with Markov chain Monte Carlo methods of computation. In comparison with a standard statistical approach, our model is advantageous because, exploiting all the information gleaned from the patient as it is gradually made available, it is capable to detect even small prognostic effects.

Prognosis of myasthenia gravis: a retrospective study of 380 patients.

The 9139 follow-up records of 438 myasthenia gravis (MG) patients were reviewed. Excluding those patients who were diagnosed 5 or more years after symptom onset (n = 37) and those who experienced only oculomotor symptoms throughout follow-up (n = 21), there were 380 patients. A survival analysis approach was used to assess the influence of prognostic factors on the following endpoints: (a) stable complete remission, (b) complete remission of at least 6 months and (c) pharmacological remission of at least 6 months. Early diagnosis was associated with a better prognosis with respect to all endpoints. Thymectomy also improved the prognosis but only for those patients without thymoma. Later MG onset was associated with a higher tendency to achieve pharmacological remission.

Value of right ventricular ejection fraction in predicting short-term prognosis of patients with severe chronic heart failure.

BACKGROUND: The prognosis of chronic heart failure has been studied extensively, but factors predicting short-term outcome in patients with severe chronic heart failure are still poorly defined, and the current indications for heart transplantation as a treatment for end-stage heart failure need on objective analysis. METHODS: Purpose of the study was to identify the determinants of short-term prognosis in a group of 142 consecutive ambulatory patients (mean age 49.8 +/- 11 years). Referred for heart transplantation because of severe chronic heart failure, the patients were admitted with left ventricular ejection fraction markedly depressed and had had symptoms in spite of an optimal standardized medical therapy for at least 1 month. Baseline clinical and instrumental evaluation included right-sided heart catheterization with a flow-directed multilumen thermodilution catheter, which enables determination of pressures, cardiac output, right ventricular volumes, and ejection fraction. RESULTS: Most patients were in New York Heart Association class III (61%) and IV (24%), and the hemodynamic profile was characterized by mean left ventricular ejection fraction of 20.2% +/- 6%, cardiac index of 2.13 +/- 0.6 l/min/m2, pulmonary capillary wedge pressure of 23.1 +/- 11 mm Hg, right atrial pressure of 7.9 +/- 6 mm Hg, right ventricular ejection fraction of 23.2% +/- 12.4%. During a mean follow-up of 11.1 +/- 9.4 months, 33 patients underwent transplantation (23.4%), 41 died (28.8%), and 68 were still alive (47.8%). There was a substantial overlap in left ventricular ejection fraction between patients divided on the basis of outcome, whereas right ventricular ejection fraction was significantly lower in patients who died or underwent transplantation. Cox multivariate analysis showed three independent prognostic variables: cause (p = 0.03), heart failure score (p = 0.001), and right ventricular ejection fraction (p = 0.000). Short-term survival (10 months) was significantly (p = 0.000) different in patients with > or = 24% or < 24% right ventricular ejection fraction. Statistical analysis identified right ventricular ejection fraction as the single variable to be highly correlated with an increased risk of early death. CONCLUSIONS: This study suggests that right ventricular function is a crucial determinant of short-term prognosis in severe chronic heart failure. Statistical analysis identified right ventricular ejection fraction, determined by thermodilution during right-sided heart catheterization, as the single most important predictor of short-term prognosis in a large cohort of patients who had symptoms in spite of a standardized, optimized, multipharmacologic treatment. The variable allows a useful risk stratification in patients with severe chronic heart failure and uniformly depressed left ventricular ejection fraction and provides guidance in the assessment of indications and timing for transplantation.

Interaction between exercise training and ejection fraction in predicting prognosis after a first myocardial infarction.

BACKGROUND: Although recent meta-analysis trials have shown that exercise training may improve survival after myocardial infarction, the mechanism of this beneficial effect is still unknown. The purpose of this study was to detect possible interactions between exercise training and predictors of prognosis after a first myocardial infarction. METHODS AND RESULTS: Patients with uneventful clinical courses after a first myocardial infarction were randomly assigned to a 4-week training period (125 patients, group 1) or to a control group (131 patients, group 2). Before randomization, all patients underwent a symptom-limited exercise test (28 +/- 2 days after myocardial infarction), 24-hour Holter monitoring, and coronary arteriography (31 +/- 3 days after the acute episode). After a mean follow-up period of 34.5 months, 18 patients had cardiac deaths (5 in group 1 and 13 in group 2). Multivariate analysis by Cox regression model showed that ejection fraction was the only independent prognostic indicator (P = .03). Evidence existed of an interaction between ejection fraction and exercise training, showing an effect of physical training on survival that depended on the patient's ejection fraction. Among patients with ejection fractions < 41%, the relative risk for an untrained patient was 8.63 times higher than for a trained patient (P = .04), whereas for ejection fractions > 40%, the estimated risks for trained and untrained patients were similar. CONCLUSIONS: These data show that exercise training may prolong survival in post-myocardial infarction patients with depressed left ventricular function. A randomized trial in such patients seems warranted.

[Recovery time from myocardial ischemia induced by exercise test: correlation with duration of ischemia during the test and with the extent of coronary disease]. / Tempo di recupero dall'ischemia miocardica indotta mediante test da sforzo: correlazione con la durata dell'ischemia durante il test e con l'estensione della malattia coronarica.

BACKGROUND: Aim of this study was to evaluate the factors affecting the duration of the recovery time (RT) after a positive exercise stress test and to define its relationship with the extent of coronary artery disease (CAD). METHODS: We studied 109 consecutive patients with a positive exercise test and proven coronary disease. RESULTS: RT was neither related to the severity of CAD, nor to exercise duration, rate-pressure product at the end of the exercise and maximum ST segment depression. A significant linear relationship was found between RT and the time of ischemia during exercise (IT) (r = 0.66, p < .001). This relationship was analyzed separately in patients (pts) with advanced (Group I) and in pts with less severe CAD (Group II). The regression line of the data showed a similar slope but a higher y-axis intercept in Group I than in Group II (p < .05). The RT/IT ratio was in fact significantly higher in Group I than in Group II (3.0 +/- 1.3 vs 1.7 +/- 0.7, p < .0001). Discriminant analysis was performed to predict the presence of advanced CAD: using the RT/IT ratio instead of RT correct classification rate of the model increased from 81.4 to 86.7%, predictive accuracy from 73.7 to 85.3% and true negative rate from 85.3 to 87.4%. CONCLUSIONS: These results suggest that the normalization of the recovery time by time of ischemia during the test provides a simple and useful index for the prediction of the extent of coronary artery disease.

Bayesian analysis of survival on multiple time scales.

We propose a Bayesian approach to the analysis of survival data on multiple time scales. Non-parametric modelling of variation of rates with more than one time scale is achieved using priors which specify smooth variation. Computations are conveniently carried out using Gibbs sampling. We discuss the extension of the method to Bayesian forecasting of rates. Numerical experience of two examples is described.

Predictors of prognosis in patients awaiting heart transplantation.

Patients enrolled in a clinical heart transplantation program were evaluated to identify the predictors of prognosis in patients with advanced heart disease and to optimize timing of heart transplantation. Three hundred eighty-eight subjects were consecutively evaluated from 1985 through 1989. One hundred eighty-four patients (47.5%) had dilated cardiomyopathy; 164 patients (42.2%) had ischemic heart disease; 34 patients (8.8%) had valvular heart disease, and six patients (1.5%) had miscellaneous disorders. In each patient, 45 different parameters were considered. During follow-up (mean, 8.4 months) 166 patients underwent heart transplantation; 99 patients died (heart failure, 66 patients; sudden death, 26 patients; thromboembolism, two patients; noncardiac causes, five patients). The actuarial survival was 83% at 3 months, 77% at 6 months, 73% at 9 months, 70% at 1 year, and 59% at 2 years. The median survival time was 28 months. Analysis by Cox proportional hazard regression model revealed seven independent and significant prognostic factors: etiology (p < 0.05), NYHA class (p < 0.05), third heart sound (p < 0.05), diastolic pulmonary artery pressure (p < 0.05), pulmonary wedge pressure (p < 0.01), mean systemic blood pressure (p < 0.05), and cardiac output (p < 0.05). Cox's analysis allows the computation of patient-specific curves for predictions of residual survival time at any moment during follow-up. Moreover it can be used to calculate a simple prognostic index, which enables stratification of the patient population into three risk classes: patients at high (n = 105), intermediate (n = 160) and low (n = 123) risk of early death. Pairwise comparisons of survival between the classes were significant at 1% level.

Right ventricular failure after heart transplantation: relationship with preoperative haemodynamic parameters.

The prevalence of right ventricular failure after orthotopic heart transplantation, evaluated in 196 patients, was 11.7%, as assessed by the presence during the first postoperative month of right atrial pressure > 10 mm Hg. Two deaths, related to refractory right ventricular failure, were observed within the first month, both in subjects with preoperative pulmonary arteriolar resistances > 5 Wood Units. The haemodynamic profile after heart transplantation showed a significant decrease (P < 0.01) and an early normalization of pulmonary arterial pressure, pulmonary wedge pressure and pulmonary arteriolar resistances, while right atrial pressure slowly decreased until the third month. In a long-term analysis of survival (death within 1 year) the probability of death was significantly related to the values of right atrial pressure and cardiac index during the first month after heart transplantation. Otherwise, the presence of elevated values of right atrial pressure did not show a significant correlation with the echocardiographic right ventricular end-diastolic diameter nor with the presence of right bundle branch block. The careful selection of patients referred for the cardiac transplantation (mean value of pulmonary arteriolar resistances in the evaluated subjects was 2.5 +/- 1.5 Wood Units) improves the probability of avoiding the appearance of severe right ventricular failure in the postoperative period in most cases. The best predictor of right ventricular failure remains to be clearly identified.

GAMEES: a probabilistic environment for expert systems.

This paper describes GAMEES (Graphical Modelling Environment for Expert Systems), an interactive graphical environment for building and processing Belief Networks and Influence Diagrams. We review the existing systems designed for analogous purposes, and, after a brief introduction to Belief Networks and Influence Diagrams, we describe the graphical interface, discuss algorithms for probabilistic inference on these networks and illustrate the current implementation of GAMEES. The system has been designed for being integrated within wider expert systems and actually it is part of the Therapy Advisor module within an expert system for the management of anemic patients.

Long-term survival and risk stratification in patients with angina at rest undergoing medical treatment.

In order to determine those factors which influence long-term prognosis in patients with angina at rest associated with transient ST-segment changes, 217 patients undergoing medical treatment were followed for a mean of 39 months. All patients underwent coronary arteriography. Univariate analysis identified 12 variables significantly related to prognosis. These were disease of the left main coronary artery; the number of diseased vessels; left ventricular end-diastolic pressure; ejection fraction; baseline electrocardiogram; presence of prior myocardial infarction; ST-segment depression and ventricular arrhythmias during pain; disease of the proximal anterior descending coronary artery; crescendo angina; hypertension; and age. Use of the Cox regression model for survival analysis revealed only 3 variables which were independent predictors of prognosis. They were disease of the left main coronary artery; the number of diseased vessels and left ventricular end-diastolic pressure. The model allowed stratification of patients into 3 groups. Survival at 3 years was 98% in the low risk group; 82% in the intermediate risk group; and 58% in the high risk group. These data indicate that disease of the left main coronary artery, the number of diseased vessels and left ventricular end-diastolic pressure are the independent predictors of prognosis in angina at rest. These variables may allow stratification of patients into groups having different long-term survivals.

A prognostic classification of myelofibrosis with myeloid metaplasia.

The dependence of survival time on a set of prognostic factors was explored by means of Cox's regression model in 137 cases of myelofibrosis with myeloid metaplasia (MMM). The following parameters recorded at diagnosis proved to be important independent indicators of a poor prognosis: a higher value for age, a lower value for Hb concentration, a higher value for immature myeloid cells in peripheral blood (IMC), a lower value for total erythroid iron turnover (TEIT), and a bone marrow red cell aplasia (RCA). A prognostic classification tree was constructed whose terminal nodes (risk groups), described by simple logical conditions upon important indicators, were characterized by significantly different expected survival. The two extreme risk groups lend themselves to a simple, but complete description. The low-risk group (19.7% of the sample) comprises cases who had the diagnosis of MMM before age 45 and a number of IMC constantly lower than 24%. The actuarial proportion of patients surviving at 15 years was 100%. The high-risk group (29.9% of cases) comprises patients with age greater than 45 and Hb lower than 13 g/dl, associated with RCA, or with a relatively decreased erythropoiesis (TEIT lower than 2 times the normal) or with IMC greater than 24%. Seven out of the 11 who died within this group developed blastic crisis. Median survival time of the group was 69 months.

Effects of surgical versus medical treatment on long-term prognosis in angina at rest: an observational non-randomized study of 400 patients.

The effect of surgical versus medical treatment on long-term prognosis in angina at rest was assessed using the Cox regression model for survival analysis in 400 patients complaining of recurrent episodes of resting chest pain associated with transient repolarization changes. The surgical group included 185 patients, and the medical group 215. Surgically treated patients more frequently had two- and three-vessel disease, while single-vessel disease prevailed in medically treated patients (P less than 0.01). No difference between the two groups was found in mean values of left ventricular end diastolic pressure and ejection fraction. Three variables were identified as independent predictors of prognosis in all patients: left ventricular end-diastolic pressure (P less than 0.001), age greater than 45 years (P less than 0.05), and number of diseased vessels (P less than 0.05). Treatment modality did not result in different long-term survival in the entire population. However, patients with three-vessel disease had a better outcome with surgical than with medical therapy (P less than 0.05). Although our conclusions must be tempered by consideration of the limitations of non-randomized studies, these results show that surgical treatment may improve survival in patients with angina at rest and three-vessel disease.

Classification of anaemia on the basis of ferrokinetic parameters.

Quantitative information on abnormalities of erythropoiesis and mechanisms of anaemia has been obtained in 136 anaemic patients by means of ferrokinetic studies. To derive a functional classification of anaemia based on ferrokinetic parameters, agglomerative hierarchical cluster analysis and principal coordinate analysis were utilized as techniques for unsupervised classification. Two main clusters were found and named anaemia with low potential erythropoiesis and with high potential erythropoiesis, since the most discriminant parameter between them was total erythroid iron turnover, a measure of total erythropoietic activity. A value of total erythropoiesis equal to 4 times the normal was found to discriminate these two types of anaemia in 94% of cases. Within the group with low potential erythropoiesis, three clusters showing different qualitative disturbances of erythropoiesis were singled out. Among patients with high potential erythropoiesis, two clusters were found. A value of effective erythropoiesis equal to 2.5 times the normal was shown to have a high discriminant power between these clusters. This threshold level distinguished between patients having ineffective erythropoiesis or peripheral haemolysis as the major mechanism of anaemia. The present functional classification of anaemia provides a complete picture of the different pathogenetic mechanisms and may represent the basis for a more rational diagnostic approach to erythroid disorders.